𝗧𝗵𝗲 𝗔𝗜 𝗧𝗮𝗰𝗸𝘀 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 𝗧𝗿𝘂𝘀𝘁 𝗔𝗻𝗱 𝗧𝗵𝗲 𝗢𝗻𝗲𝘀 𝗧𝗵𝗲𝘆 𝗗𝗼𝘂𝗯𝗹𝗲-𝗖𝗵𝗲𝗰𝗸 You need to know when to trust AI-generated code and when to double-check it.
- AI tools can help with tasks like boilerplate code and test stubs.
- But you should review code for complex tasks like error handling and security-sensitive code.
Here are some tasks and the trust levels for AI-generated code:
- Commit messages: trust
- README/docs draft: trust
- Boilerplate/scaffolding: trust
- Regex (standard formats): trust
- CSS/layout: trust
- Test stubs/mock data: review
- Data transformation: review
- Explaining unfamiliar code: review
- ORM reads/simple queries: review
- Unit test logic: review
- Well-documented API: review
- Error handling/edge cases: always review
- Recent library versions: always review
- Async/concurrency logic: always review
- Null/type handling: always review
- Write/update/delete queries: always review
- Auth/authorization logic: always review
- Niche/undocumented APIs: always review
- Security-sensitive code: always review
- Compliance/PII/GDPR logic: never skip
Source: https://dev.to/preetid/the-ai-tasks-developers-trust-and-the-ones-they-double-check-553b Optional learning community: https://t.me/GyaanSetuAi